Towards Improving English-Latvian Translation: A System Comparison and a New Rescoring Feature

Maxim Khalilov, José A. R. Fonollosa, Inguna Skadin̨a, Edgars Brālītis, Lauma Pretkalnin̨a


Abstract
Translation into the languages with relatively free word order has received a lot less attention than translation into fixed word order languages (English), or into analytical languages (Chinese). At the same time this translation task is found among the most difficult challenges for machine translation (MT), and intuitively it seems that there is some space in improvement intending to reflect the free word order structure of the target language. This paper presents a comparative study of two alternative approaches to statistical machine translation (SMT) and their application to a task of English-to-Latvian translation. Furthermore, a novel feature intending to reflect the relatively free word order scheme of the Latvian language is proposed and successfully applied on the n-best list rescoring step. Moving beyond classical automatic scores of translation quality that are classically presented in MT research papers, we contribute presenting a manual error analysis of MT systems output that helps to shed light on advantages and disadvantages of the SMT systems under consideration.
Anthology ID:
L10-1154
Volume:
Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)
Month:
May
Year:
2010
Address:
Valletta, Malta
Venue:
LREC
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Publisher:
European Language Resources Association (ELRA)
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URL:
http://www.lrec-conf.org/proceedings/lrec2010/pdf/228_Paper.pdf
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Cite (ACL):
Maxim Khalilov, José A. R. Fonollosa, Inguna Skadin̨a, Edgars Brālītis, and Lauma Pretkalnin̨a. 2010. Towards Improving English-Latvian Translation: A System Comparison and a New Rescoring Feature. In Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10), Valletta, Malta. European Language Resources Association (ELRA).
Cite (Informal):
Towards Improving English-Latvian Translation: A System Comparison and a New Rescoring Feature (Khalilov et al., LREC 2010)
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http://www.lrec-conf.org/proceedings/lrec2010/pdf/228_Paper.pdf